CN110646373A - Method for measuring sugar content of tobacco flavor and fragrance - Google Patents
Method for measuring sugar content of tobacco flavor and fragrance Download PDFInfo
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- 239000000796 flavoring agent Substances 0.000 title claims abstract description 57
- 235000019634 flavors Nutrition 0.000 title claims abstract description 57
- 241000208125 Nicotiana Species 0.000 title claims abstract description 51
- 235000002637 Nicotiana tabacum Nutrition 0.000 title claims abstract description 51
- 239000003205 fragrance Substances 0.000 title claims abstract description 43
- 238000000034 method Methods 0.000 title claims abstract description 41
- 239000011159 matrix material Substances 0.000 claims abstract description 206
- 238000001228 spectrum Methods 0.000 claims abstract description 49
- 235000013599 spices Nutrition 0.000 claims abstract description 32
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 7
- 230000003595 spectral effect Effects 0.000 claims description 64
- 238000012360 testing method Methods 0.000 claims description 19
- 235000019504 cigarettes Nutrition 0.000 claims description 10
- 238000012545 processing Methods 0.000 claims description 10
- 230000005540 biological transmission Effects 0.000 claims description 5
- 230000003287 optical effect Effects 0.000 claims description 5
- 238000010606 normalization Methods 0.000 claims description 2
- 239000002304 perfume Substances 0.000 abstract description 7
- 238000001514 detection method Methods 0.000 abstract description 2
- 238000013178 mathematical model Methods 0.000 abstract 2
- 238000004566 IR spectroscopy Methods 0.000 abstract 1
- 238000012937 correction Methods 0.000 description 7
- 238000001069 Raman spectroscopy Methods 0.000 description 5
- 238000012795 verification Methods 0.000 description 5
- 230000000694 effects Effects 0.000 description 3
- 238000002835 absorbance Methods 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 238000007781 pre-processing Methods 0.000 description 2
- 238000003908 quality control method Methods 0.000 description 2
- 238000007430 reference method Methods 0.000 description 2
- 241000989913 Gunnera petaloidea Species 0.000 description 1
- 238000004497 NIR spectroscopy Methods 0.000 description 1
- 238000005102 attenuated total reflection Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000002790 cross-validation Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000011065 in-situ storage Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 230000000391 smoking effect Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3577—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing liquids, e.g. polluted water
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- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
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- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
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- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/65—Raman scattering
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- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N2021/3595—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using FTIR
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Abstract
The invention discloses a method for measuring the sugar content of a tobacco flavor, which obtains a spectrum matrix and a numerical matrix of a flavor sample by obtaining an infrared spectrogram of the tobacco flavor and the sugar content value of the tobacco flavor, obtaining the spectrum matrix component and the numerical matrix component of which the spectrum matrix and the numerical matrix accord with the maximum variance through a partial least square method, establishing a corresponding mathematical model of the sugar content value of the tobacco flavor and fragrance and the near-infrared spectrogram according to all the obtained spectrum matrix components and numerical matrix components, for the essence and spice with the sugar content needing to be measured, the sugar content value of the essence and spice can be obtained only by obtaining the infrared spectrum numerical value doctor mathematical model, the method of the invention is simple, the infrared spectrogram of the tobacco essence perfume can be accurately obtained through the infrared spectroscopy, the detection precision is high, and the determination of the sugar content of the tobacco essence perfume can be quickly and accurately realized.
Description
Technical Field
The invention relates to the technical field of tobacco, in particular to a method for measuring the sugar content of tobacco flavor and fragrance.
Background
The tobacco essence perfume has the functions of improving the smoking quality of cigarettes and endowing the cigarettes with characteristic fragrance, and is an important factor forming the brand style of the cigarettes. Whether the quality of different batches of essence and spice products is stable or not is closely related to the quality stability of cigarette products. However, the complexity and diversity of chemical components of the formed flavors and fragrances are always the key and difficult points of quality control due to the influence of various factors such as raw materials and processing. Therefore, it is necessary to perform a comprehensive evaluation on the quality of the flavor for tobacco, wherein the sugar content index for evaluating whether the quality of the flavor is stable includes total sugar and reducing sugar. At present, the measurement of total sugar and reducing sugar of flavors and fragrances in the tobacco industry does not form a standard.
Disclosure of Invention
The invention aims to provide a method for measuring the sugar content of tobacco flavor and fragrance, which overcomes the defects of the prior art.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for measuring the sugar content of flavor and fragrance for cigarettes comprises the following steps:
step 1), acquiring an infrared spectrogram of a flavor and fragrance sample, and acquiring a spectral matrix E of the flavor and fragrance sample according to the acquired infrared spectrogram;
step 2), obtaining the sugar content value of the essence and spice sample, and establishing a sugar content numerical matrix F of the essence and spice sample according to the sugar content value of the essence and spice sample;
step 3), establishing a sugar content model of the tobacco flavor and fragrance based on a partial least square method:
standardizing the spectrum matrix E to obtain the standardized spectrum matrix EiStandardizing the sugar content numerical matrix F to obtain a standardized sugar content numerical matrix FiIn the spectral matrix EiExtracting the spectral matrix component tiIn a matrix F of sugar content valuesiExtracting the sugar content numerical value matrix component uiMaking the acquired spectral matrix component tiWith the component u of the numerical matrix of sugar contentiThe maximum variance is met, i.e.:
Cov(ti,ui)–>max；
cov is the covariance sign, max is the maximum sign;
establishing spectral matrix components tiWith the component u of the numerical matrix of sugar contentiMaximum variance expression of (2):
max<EiWi+1,FiCi+1>；
Wi+1is a spectral weight coefficient, Ci+1Is a numerical weight coefficient;
obtaining W through Lagrange solutioni+1And Ci+1Value, where Wi+1||＝1；||Ci+1||＝1,i≥0；
According to Wi+1And Ci+1The spectrum matrix component t with the maximum variance is obtained by inverse solutioniWith the component u of the numerical matrix of sugar contenti；
According to the obtained spectral matrix component tiEstablishing a spectral matrix EiSpectral residual matrix E ofi-1For the spectral matrix component tiAccording to the component u of the sugar content numerical matrixiEstablishing a sugar content numerical matrix FiNumerical residual matrix F ofi-1For sugar content numerical matrix component uiThe regression equation of (a):
wherein:
in the formula, piIs a spectral matrix EiOf the ith load vector, qiIs a sugar content numerical matrix FiOf the ith load vector, riIs tiAnd uiThe relationship vector of (1);
obtaining a spectrum residual error matrix E according to the abovei-1Sum value residual error matrix Fi-1Obtaining a spectral matrix component ti-nSugar content numerical matrix component ui-nSpectrum residual matrix Ei-nSum value residual error matrix Fi-n，nThe amount of the main components of the sugar content;
according to the acquired spectral matrix component ti-nAnd a sugar content value matrix component ui-nEstablishing a spectral matrix EiAnd sugar content numerical matrix FiThe regression expression of (1):
a is a spectral matrix EiAnd sugar content numerical matrix FiThe rank of (d); t is t1,…,tARepresents E1，E2，…，EAThe linear combination of (a) and (b),
obtaining a sugar content expression:
in the formula, y*Is a value of sugar content, F(i-n)kAs a numerical residual matrix Fi-nThe kth line of (1); wherein { ak1,ak2,...,akmThe values of the regression coefficients are obtained; x is the number of1，x2，…，xmThe infrared spectrum data value of the essence and spice to be detected is obtained; substituting the infrared spectrum data value of the essence and spice to be detected into the sugar content expression to obtain the sugar content value of the essence and spice to be detected.
Further, in the step 1), the essence and spice sample is dropped on an optical bench for infrared test or Raman test, so as to obtain an infrared spectrogram or Raman spectrogram of the essence and spice for the cigarette.
Further, the infrared test comprises a near infrared test and a mid-infrared test, and the parameters of the spectrometer adopting the near infrared test are as follows: the scanning times are 4-256 times, and the resolution is 4cm-1～64cm-1Wavelength range of 10000cm-1～4000cm-1(ii) a The spectrometer parameters for mid-infrared testing were: the scanning times are 2-256 times, and the resolution is 1cm-1～64cm-1Wavelength range 4000cm-1～400cm-1。
Furthermore, the infrared spectrogram collection mode comprises transmission, diffuse reflection and diffuse transflectance.
Further, in the step 2), a continuous flow analyzer is adopted to determine the sugar content value of the tobacco flavor and fragrance.
Further, in step 3), data standardization processing is performed on the spectral matrix E to obtain a standardized spectral matrix Ei(n × m), n is the number of samples, and m is the dimension.
Further, subtracting the mean value of a dimension variable from each spectrum matrix and dividing the mean value by the standard deviation of the dimension to complete the spectrum matrix EiThe data normalization process of (1).
Further, the data matrix obtained by carrying out data standardization processing on the sugar content numerical value matrix F is recorded as Fi(n×p)，p＝1。
Furthermore, the data standardization processing of the sugar content numerical value matrix can be completed by subtracting the mean value of a dimension variable from each sugar content numerical value matrix and dividing the mean value by the standard deviation of the dimension.
Compared with the prior art, the invention has the following beneficial technical effects:
the invention relates to a method for measuring the sugar content of tobacco flavor and spice, which comprises the steps of obtaining an infrared spectrogram of the tobacco flavor and spice and the sugar content value of the tobacco flavor and spice to obtain a spectrum matrix and a sugar content numerical matrix of a flavor and spice sample, establishing a sugar content model of the tobacco flavor and spice based on a partial least square method according to the spectrum matrix and the sugar content numerical matrix, obtaining a spectrum matrix component and a sugar content numerical matrix component of which the spectrum matrix and the sugar content numerical matrix meet the maximum variance through the partial least square method, and then sequentially obtaining a spectrum matrix component and a sugar content numerical matrix component of the residual main component quantity through a residual error matrix after removing the spectrum matrix component and the sugar content numerical matrix component which meet the maximum variance, wherein the sugar has great influence on the peak intensity of the infrared spectrogram for tobacco and obviously corresponds to the sugar content value, so that the sugar content value and the infrared spectrogram for the tobacco flavor can be accurately established corresponding to the sugar content value The method is simple, can continuously measure the flavors and fragrances of different brands, can accurately obtain the spectrogram of the tobacco flavor and fragrance by the spectrum method, has high detection precision, and can quickly and accurately realize the determination of the sugar content of the tobacco flavor and fragrance.
Drawings
FIG. 1 is a flow chart of the present invention.
FIG. 2 is a spectrum of a sample of the tobacco flavor and fragrance of example 1 of the present invention.
FIG. 3 is a spectrum of a sample of the tobacco flavor and fragrance of example 2 of the present invention.
Detailed Description
The invention is described in further detail below with reference to the accompanying drawings:
as shown in figure 1, the method for measuring the sugar content of the tobacco flavor and fragrance comprises the following steps:
step 1), obtaining a spectrogram of a flavor and fragrance sample, and obtaining a spectral matrix E of the flavor and fragrance sample according to the obtained spectrogram;
specifically, the essence and spice sample is dropped on an optical bench for infrared test or Raman test, and an infrared spectrogram or Raman spectrogram of the essence and spice for the cigarette is obtained.
Specifically, a mid-infrared test or a near-infrared test is adopted, and the parameters of a spectrometer adopting the near-infrared test are as follows: the scanning times are 4-256 times, and the resolution is 4cm-1～64cm-1Wavelength range of 10000cm-1～4000cm-1(ii) a The spectrometer parameters for mid-infrared testing were: the scanning times are 2-256 times, and the resolution is 1cm-1～64cm-1Wavelength range 4000cm-1～400cm-1(ii) a The spectrometer parameters for raman testing were: the scanning times are 2-64 times, the integration time is 500-5000 ms, and the wavelength range is 152cm-1～2488cm-1。
The infrared spectrogram collecting mode comprises attenuated total reflection, transmission, diffuse reflection and diffuse transflection;
step 2), obtaining the sugar content value of the essence and spice sample, and establishing a sugar content numerical matrix F of the essence and spice sample according to the sugar content value of the essence and spice sample;
specifically, determining the sugar content value of the tobacco essence perfume based on a constant-temperature water bath;
step 3), respectively establishing a sugar content model of the tobacco flavor and fragrance based on a partial least square method: combining the spectrum matrix of the essence and spice sample with the sugar content numerical value matrix to establish a sugar content model of the essence and spice for the cigarette;
firstly, carrying out data standardization processing on the spectrum matrix E to obtain the spectrum matrix E after standardization processingi(nxm), wherein n is the number of samples, and m is the dimensionality;
the data matrix after the sugar content numerical value matrix F is subjected to data standardization treatment is recorded as Fi(n×p，p＝1)；
Specifically, the method comprises the following steps: and (3) carrying out data standardization processing on the spectral matrix E: that is, the mean value of one dimension variable subtracted from each spectrum matrix is divided by the standard deviation of the dimension to complete the spectrum matrix EiThe data standardization processing of (2);
specifically, the method comprises the following steps: and (3) carrying out data standardization treatment on the sugar content numerical value matrix F: that is, the average value of a dimension variable subtracted from each sugar content numerical matrix is divided by the standard deviation of the dimension to complete the sugar content numerical matrix FiThe data standardization processing of (2);
in the spectral matrix EiExtracting the spectral matrix component tiIn a matrix F of sugar content valuesiExtracting the sugar content numerical value matrix component ui；
Sugar content value matrix FiSpecifically, a sugar content value and a sugar content numerical matrix of a flavor and fragrance sample;
the spectrum matrix EiAs an independent variable matrix, each row is a spectrum, and each column is a dimension variable;
the sugar content numerical value matrix FiAs dependent variable matrix, sugar content numerical matrix FiOnly one column;
calculating the spectral matrix component t meeting the maximum varianceiWith the component u of the numerical matrix of sugar contentiNamely:
Cov(ti,ui)–>max；
cov is the covariance sign, max is the maximum sign;
spectral matrix component tiIs a spectral matrix EiLinear combination of, i.e. ti＝EiWi+1，Wi+1Is a spectral weight coefficientSugar content numerical matrix component uiIs a matrix F of numerical values of sugar contentiLinear combination of (1), ui＝FiCi+1，Ci+1Is a numerical weight coefficient, Wi+1And Ci+1The same is a unit vector;
establishing spectral matrix components tiWith the component u of the numerical matrix of sugar contentiThe maximum variance of (c) is expressed as:
max<EiWi+1,FiCi+1>
Wi+1is a matrix Ei＇FiFi＇EiThe eigenvector corresponding to the largest eigenvalue, Ci+1Is a matrix Fi＇EiEi＇Fi+1The maximum eigenvector corresponding to the maximum eigenvalue can be solved by Lagrange to obtain Wi+1And Ci+1Value, Wi+1And Ci+1Are uniformly unitized, wherein | | Wi+1||＝1；||C i+11 haha, fun, that is, the situation is different;
according to the acquired Wi+1And Ci+1The spectrum matrix component t with the maximum variance is obtained by inverse solutioniWith the component u of the numerical matrix of sugar contenti(ii) a According to the acquired spectral matrix component tiWith the component u of the numerical matrix of sugar contentiEstablishing a regression equation:
according to the obtained spectral matrix component tiEstablishing a spectral matrix EiSpectral residual matrix E ofi-1For the spectral matrix component tiAccording to the component u of the sugar content numerical matrixiEstablishing a sugar content numerical matrix FiNumerical residual matrix F ofi-1For sugar content numerical matrix component uiThe regression equation of (a):
in the formula, piIs a spectral matrix EiOf the ith load vector, qiIs a sugar content numerical matrix FiOf the ith load vector, riIs tiAnd uiThe relationship vector of (1); ei-1Is a spectral matrix EiSpectral residual matrix of (F)i-1Is a sugar content numerical matrix FiThe numerical residual matrix of (2);
the regression coefficient vector is calculated as follows:
spectral residual matrix Ei-1I.e. from the spectral matrix EiRemoving solved spectral matrix component tiThe residual spectrum matrix and the numerical residual error matrix Fi-1I.e. from the sugar content value matrix FiRemoving solved sugar content numerical value matrix component uiThe value matrix of the residual sugar content;
from the spectral residual matrix E, respectivelyi-1Sum value residual error matrix Fi-1Extracting the spectral matrix component t meeting the maximum variance requirementi-1And a sugar content value matrix component ui-1Establishing a spectrum residual error matrix Ei-1Spectral residual matrix E ofi-2For the spectral matrix component ti-1To establish a numerical residual matrix Fi-1Numerical residual matrix F ofi-2For sugar content numerical matrix component ui-1To obtain a spectrum residual error matrixEi-2Sum value residual error matrix Fi-2Repeating the above steps to obtain the spectral matrix component ti-nSugar content numerical matrix component ui-nSpectrum residual matrix Ei-nSum value residual error matrix Fi-n，nThe amount of the main components of the sugar content;
spectral residual matrix Ei-2I.e. from the spectral matrix Ei-1Removing solved spectral matrix component ti-1The residual spectrum matrix and the numerical residual error matrix Fi-2I.e. from the sugar content value matrix Fi-1Removing solved sugar content numerical value matrix component ui-1The value matrix of the residual sugar content;
according to the acquired spectral matrix component ti-nAnd a sugar content value matrix component ui-nEstablishing a spectral matrix EiAnd sugar content numerical matrix FiThe regression expression of (1):
a is a spectral matrix EiAnd sugar content numerical matrix FiThe rank of (d); t is t1,…,tARepresents E1，E2，…，EAThe linear combination of (a) and (b),
obtaining a sugar content expression:
in the formula, y*Is a value of sugar content, F(i-n)kAs a numerical residual matrix Fi-nThe kth line of (1); wherein { ak1,ak2,...,akmThe values of the regression coefficients are obtained; x is the number of1，x2，…，xmThe infrared spectrum data value of the essence and spice to be detected is obtained; replacing infrared spectrum data value of essence and spice to be detectedAnd adding the sugar content expression to obtain the sugar content value of the essence and spice to be detected. The sugar content comprises a total sugar content value and a reducing sugar content value, and the total sugar content value and the reducing sugar content value are respectively measured.
The invention evaluates and establishes model accuracy through a correction decision coefficient (R2_ Cal), a prediction decision coefficient (R2_ Pre), a cross validation Root Mean Square Error (RMSECV) and a prediction Root Mean Square Error (RMSEP):
r2_ Cal and R2_ PRE are calculated as follows:
the RMSECV calculation is as follows:
the RMSEP calculation formula is as follows:
in the formula, yi,actualThe measured values of the total sugar and reducing sugar of the tobacco flavor and fragrance are collected for the ith correction set or verification set;
the average value of the sample measured values of the correction set or the verification set of the method; y isi,predictedThe method is a predicted value of the ith sample in the prediction process, n is the spectrum number of the sample in the correction set, and m is the spectrum number of the sample in the verification set.
Generally, the closer R2_ Cal and R2_ Pres are to 1, the better, the closer RMSECV and RMSEP are to 0, the better.
Example 1
The adopted equipment, Thermo Fisher iS5N, iS a Fourier transform near infrared spectrometer, and a diffuse transmission method iS adopted for testing sample spectrum accessories, the optical path iS 1mm, and the wavelength range iS 10000cm-1～4000cm-1. The resolution of the instrument is 16cm-1The number of scans was 48. Cigarette participating in modelingTotal 374 batches with perfume.
The result of the spectrum of the tobacco flavor sample is shown in fig. 2, and it can be found that the phenomenon of absorbance saturation absorption exists in the repeated spectrum in a part of wave number intervals, and in order to enhance the robustness of the model, the area of absorbance saturation absorption is removed. And establishing a relation between the spectral data and the actually measured data of the corresponding reference method by using the TheUnscamblebler partial least square module. The calibration set is used for establishing a model, the verification set is used for verifying the model, and the model is evaluated according to four indexes of R2_ Cal, R2_ Pre, RMSECV and RMSEP, and the results are shown in the following table 1. It can be found that R2_ Cal and R2_ Pre are close to 1, and RMSECV and RMSEP are close to 0, which indicates that when the spectrum is not processed by the preprocessing method, the correction set model has good prediction effect and high prediction accuracy.
TABLE 1
Example 2
The adopted equipment is an Agilent Cary 630 Fourier transform intermediate infrared spectrometer and a DialPath transmission method of a test spectrum accessory liquid measurement technology, the optical path is 30 mu m, and the wavelength range is 4000-650 cm-1. The resolution of the instrument is 4cm-1The number of scans was 32.
The spectrum result of The tobacco flavor and fragrance sample is shown in fig. 3, The spectrum data is preprocessed by adopting standard normal variable transformation, and The relationship is established between The spectrum data (after being preprocessed) and The corresponding reference method data by using The partial least square module of The Unscrambler. The calibration set is used for establishing a model, the verification set is used for verifying the model, and the model is evaluated according to four indexes of R2_ Cal, R2_ Pre, RMSECV and RMSEP, and the results are shown in the following table 2. It can be found that R2_ Cal and R2_ Pre are close to 1, and RMSECV and RMSEP are close to 0, which shows that when the spectrum is processed by the preprocessing method, the correction set model has good prediction effect and high prediction accuracy.
TABLE 2
According to the implementation examples, the invention provides a novel method for rapidly determining the sugar index of the tobacco essence perfume, which is used for quality control of the tobacco essence perfume. Sampling and storing the tobacco essence and flavor, and acquiring a near-infrared spectrogram; measuring the sugar index (total sugar and reducing sugar) value of the tobacco flavor by using a continuous flow analyzer; establishing a relation between the sugar index and the spectral data by combining a partial least square method and taking the relation as a correction set model; and predicting two index values of the sample which does not participate in modeling. The model is verified by four indexes of R2_ Cal, R2_ Pre, RMSECV and RMSEP. The two examples show that the near infrared spectroscopy has good prediction capability on the sugar index of the tobacco flavor and fragrance, so that the sugar index of the tobacco flavor and fragrance can be rapidly, accurately and in situ measured.
Claims (10)
1. The method for measuring the sugar content of the tobacco flavor and fragrance is characterized by comprising the following steps of:
step 1), acquiring an infrared spectrogram of a flavor and fragrance sample, and acquiring a spectral matrix E of the flavor and fragrance sample according to the acquired infrared spectrogram;
step 2), obtaining the sugar content value of the essence and spice sample, and establishing a sugar content numerical matrix F of the essence and spice sample according to the sugar content value of the essence and spice sample;
step 3), establishing a sugar content model of the tobacco flavor and fragrance based on a partial least square method:
standardizing the spectrum matrix E to obtain the standardized spectrum matrix EiStandardizing the sugar content numerical matrix F to obtain a standardized sugar content numerical matrix FiIn the spectral matrix EiExtracting the spectral matrix component tiIn a matrix F of sugar content valuesiExtracting the sugar content numerical value matrix component uiMaking the acquired spectral matrix component tiWith the component u of the numerical matrix of sugar contentiThe maximum variance is met, i.e.:
Cov(ti,ui)–>max；
cov is the covariance sign, max is the maximum sign;
establishing spectral matrix components tiWith the component u of the numerical matrix of sugar contentiMaximum variance expression of (2):
max<EiWi+1,FiCi+1>；
Wi+1is a spectral weight coefficient, Ci+1Is a numerical weight coefficient;
obtaining W through Lagrange solutioni+1And Ci+1Value, where Wi+1||＝1；||C i+1||＝1,i≥0；
According to Wi+1And Ci+1The spectrum matrix component t with the maximum variance is obtained by inverse solutioniWith the component u of the numerical matrix of sugar contenti；
According to the obtained spectral matrix component tiEstablishing a spectral matrix EiSpectral residual matrix E ofi-1For the spectral matrix component tiAccording to the component u of the sugar content numerical matrixiEstablishing a sugar content numerical matrix FiNumerical residual matrix F ofi-1For sugar content numerical matrix component uiThe regression equation of (a):
Ei-1＝ti×p’i+Ei
Fi-1＝ui×q’i+Fi
Fi-1＝ti×r’i+Fi
wherein:
in the formula, piIs a spectral matrix EiOf the ith load vector, qiIs a sugar content numerical matrix FiOf the ith load vector, riIs tiAnd uiThe relationship vector of (1);
obtaining a spectrum residual error matrix E according to the abovei-1Sum value residual error matrix Fi-1Obtaining a spectral matrix component ti-nSugar content numerical matrix component ui-nSpectrum residual matrix Ei-nSum value residual error matrix Fi-n，nThe amount of the main components of the sugar content;
according to the acquired spectral matrix component ti-nAnd a sugar content value matrix component ui-nEstablishing a spectral matrix EiAnd sugar content numerical matrix FiThe regression expression of (1):
Ei＝tip’i+ti-1p’i-1+...+tAp’A
Fi＝tir’i+ti-1r’i-1+...+tAr’A+FA
a is a spectral matrix EiAnd sugar content numerical matrix FiThe rank of (d); t is t1,…,tARepresents E1，E2，…，EAThe linear combination of (a) and (b),
obtaining a sugar content expression:
in the formula, y*Is a value of sugar content, F(i-n)kAs a numerical residual matrix Fi-nThe kth line of (1); wherein { ak1,ak2,...,akmThe values of the regression coefficients are obtained; x is the number of1，x2，…，xmThe infrared spectrum data value of the essence and spice to be detected is obtained; substituting the infrared spectrum data value of the essence and spice to be detected into the sugar content expression to obtain the sugar content of the essence and spice to be detectedNumerical values.
2. The method for measuring the sugar content of the tobacco flavor and fragrance according to claim 1, wherein in the step 1), the tobacco flavor and fragrance sample is dropped on an optical bench for infrared test to obtain an infrared spectrogram of the tobacco flavor and fragrance.
3. The method for measuring the relative density of the tobacco flavor and fragrance as claimed in claim 2, wherein the parameters of a spectrometer adopting near infrared test are as follows: the scanning times are 4-256 times, and the resolution is 4cm-1～64cm-1Wavelength range of 10000cm-1～4000cm-1。
4. The method for measuring the relative density of the tobacco flavor and fragrance as claimed in claim 2, wherein the parameters of a spectrometer for performing mid-infrared test are as follows: the scanning times are 2-256 times, and the resolution is 1cm-1～64cm-1Wavelength range 4000cm-1～400cm-1。
5. The method for measuring the sugar content of the tobacco flavor and fragrance according to claim 2, wherein the collection modes of the infrared spectrogram comprise transmission, diffuse reflection and diffuse transflection.
6. The method for measuring the sugar content of the tobacco flavor and fragrance as claimed in claim 1, wherein in the step 2), a continuous flow analyzer is adopted to measure the sugar content value of the tobacco flavor and fragrance.
7. The method for measuring the sugar content of the tobacco flavor and fragrance according to claim 1, wherein in the step 3), the spectral matrix E is subjected to data standardization treatment to obtain the standardized spectral matrix Ei(n × m), n is the number of samples, and m is the dimension.
8. The method for measuring the sugar content of the tobacco flavor and fragrance according to claim 7The method is characterized in that the spectral matrix E can be completed by subtracting the mean value of a dimension variable from each spectral matrix and then dividing the mean value by the standard deviation of the dimensioniThe data normalization process of (1).
9. The method for measuring sugar content in tobacco flavor and fragrance according to claim 1, characterized in that a data matrix obtained by subjecting a sugar content numerical matrix F to data standardization treatment is recorded as Fi(n×p)，p＝1。
10. The method for measuring the sugar content of the flavor and fragrance for cigarettes according to claim 9, wherein the data standardization processing of the sugar content numerical matrix can be completed by subtracting the mean value of a dimension variable from each sugar content numerical matrix and dividing the mean value by the standard deviation of the dimension.
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